traffic data quality analysis james sturrock, pe, ptoe ...floating car data collection 90-100%...

Traffic Data Quality Analysis

James Sturrock, PE, PTOE, FHWA Resource Center Operations Team

Source Material Traffic Data Quality Measurementhttp://ntl.bts.gov/lib/jpodocs/repts_te/14058.htm

Seven DEADLY Misconceptions about Information Qualityhttp://www.fhwa.dot.gov/policyinformation/hpms/dataquality.cfm

Traffic Analysis Toolbox http://ops.fhwa.dot.gov/trafficanalysistools/

Traffic Data Recommendations

Air Quality Conformity Analysis Models

Transportation Planning Applications

Data Quality Attribute:1

Accuracy2

Data Quality Attribute:

Completeness

Data Quality Attribute: Validity


Timeliness


Typical Coverage

Air Quality Conformity Analysis

VMT by vehicle class, hour and functional classification

10%

At a given location 50% - Two weeks per month, 24 hours

Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent count stations

Within three years of model validation year

75% Freeways/Expressways 25% principal and minor arterials 10% collectors

VMT by hour and vehicle classification (Distribution of VMT by speed)

+- 2.5 mph At a given location 25% - one week per month, 24 hours

Up to 15% failure rate - 48-hour counts Up to 10% failure rate - permanent counts


75% Freeways/Expressways 25% principal and minor arterials 10% collectors

Traffic Demand Forecasting Models

Standard demand forecasting for Long Range Planning

Daily traffic volumes

Freeways: 7% Principal Arterials: 15% Minor Arterials: 20% Collectors: 25%

At a given location 25% - 12 consecutive hours out of 48-hour count



55-60% of freeway mileage 25% of principal arterials 15% of minor arterials 10-15% of collectors

Hourly traffic volumes

Freeways: 7% Principal Arterials: 15% Minor Arterials: 20% Collectors: 25%

At a given location 25% - 12 con-secutive hours out of 48-hour count




Vehicle occupancy 10-15%

At a given location 25% - 12 con-secutive hours out of 48-hour count



1-5% of total population (from surveys)



Accuracy2


Completeness



Timeliness


Typical Coverage


Percentage single unit trucks Percentage combination trucks

7-10% 3-5%

Minimum 25% - 12 consecutive hours out of 48-hour count Minimum 50% - 12 consecutive hours out of 24-hour count




Transit boardings and alightings by station and/or stop

15-20% 7-10% (Transit Planning)

75% of annual data collection



100% of rail boardings10% of bus route ridership from screen line data

Transit vehicle speeds by analysis time period

15-20% <5% - one peak and one off-peak route



100%



Accuracy2


Completeness



Timeliness


Typical Coverage


Free Flow link speeds 15-20%

90-100% validity for instrumented floating car data collection



100% Freeway mileage 100% Major arterial mileage 80-100% Collectors mileage 10% Local road mileage

Congested link speeds

At V/C < 1.0, 10 mph At V/C >1.0, 2.5 mph




100% Freeway mileage 100% Major arterial mileage 80-100% Collectors mileage 10% Local road mileage



Accuracy2


Completeness



Timeliness


Typical Coverage

Traffic Simulation Models



Accuracy2


Completeness



Timeliness


Typical Coverage

Traffic simulation

Traffic volumes by minute or sub-minute

2.50% 90% validityUp to 15% failure rate - portable traffic counts

Within one year of study 100% of study area

Turning movements by 15 minutes

5-10% error rate95% validity -manual traffic counts

0% failure - manual traffic counts


Free Flow link speeds 5.00%






Accuracy2


Completeness



Timeliness


Typical Coverage

Traffic simulation

Congested link speeds and delay statistics

2.50%




Queue length 95% validity -manual count

100% validity -manual count


Congestion Management

Congestion management

Corridor-level vehicle speeds and/or travel times by hour

5%



Within six months of study 100% of study area

Origin-Destination travel times by hour 5%



Within six months of study

1-5% of study area (from surveys)



Accuracy2


Completeness



Timeliness


Typical Coverage

Highway Performance Monitoring System


AADT

5-10% Urban Interstate 10% Other urban 8% Rural Interstate 10% Other Rural Mean Absolute Error

80% continuous count data 70-80% for portable machine counts (24-/48-hour counts)


Data three years old or less


K factor D factor

5-10% RMSE (relative) 1% RMSE (relative)

80% continuous count data 50% for portable machine counts (24-/48-hour counts)




Percent combination and single-unit trucks - Daily

20% RMSE 15% RMSE







Accuracy2


Completeness



Timeliness


Typical Coverage


VMT 5-10% RMSE Downward bias



Data one year old or less


Percent combination and single-unit trucks -Peak

25% RMSE 20% RMSE

80% continuous count data 50% for portable machine counts






Accuracy2


Completeness



Timeliness


Typical Coverage

Monthly Count Station Volume Reports

Monthly count station volume reports

Hourly volumes for seven consecutive days each month

2% RMSE 100% valid data 100% valid data required

Data one month old or less

<1% of total roadway mileage

AVC stations: Hourly volumes by vehicle class category

15% Single-Unit Truck Classification Error

100% valid data 100% valid data required

Data one month old or less

<1% of total roadway mileage



Accuracy2


Completeness



Timeliness


Typical Coverage

Generalized Coverage DiscussionTraffic Planning Application Typical Coverage (Generalized from above)

Air Quality Conformity Analysis 75% of Freeways, 25% of Arterials, 10% of Collectors

Traffic Demand Models 60% of Freeways, 25%of Arterials, 15% of Collectors

Traffic Simulation Models 100% of Freeways, Arterials,& Collect

Congestion Management 100% of Freeways, Arterials, &Collect

HPMS 60% of Freeways, 25% of Arterials, 15% of Collectors

Monthly Count Sta. Report <1% of Total Roadway Milage

There are seven potentially fatal misconceptions about information quality that can hamper an information quality initiative.

Worse yet, if these misconceptions are strongly held, they will hamper business effectiveness (best case) or result in business failure.

The seven deadly misconceptions are:

The seven deadly misconceptions are:1. "Information quality is data cleansing" 2. "Information quality is data assessment" 3. "Conformance to business rules is the same as data accuracy" 4. Accuracy"; and its counterpoint: Information quality is fitness for

purpose" 5. "Information quality problems are caused by information producers; and

its corollary: Information quality is produced by an information quality group"

6. "Information quality problems can be edited out by implementing business rules"

7. "Information quality is too expensive"

Congestion Patterns are DynamicPortland DTA Study Example

Speed : Space-Time diagram with trajectories

Travel Times Are DynamicPortland DTA Study Example

Change in travel time for vehicles traveling entire route between 4PM and 6PM

Original network

Changes Influence Traveler BehaviorPortland DTA Study Example

Change in travel time for vehicles traveling entire route between 4PM and 6PM

Comparison of original network to alternative network

Traffic Modeling CalibrationReference Traffic Analysis Toolbox

Determine MOEs for calibration early in process to frame data needs

Utilize Statistical Methods for determining appropriate number of runs utilizing two MOEs

Calibrate to both global and local MOEs

Calibrate, Calibrate, Calibrate!

Source Material Traffic Data Quality Measurementhttp://ntl.bts.gov/lib/jpodocs/repts_te/14058.htm

Seven DEADLY Misconceptions about Information Qualityhttp://www.fhwa.dot.gov/policyinformation/hpms/dataquality.cfm

Traffic Analysis Toolbox http://ops.fhwa.dot.gov/trafficanalysistools/

Thank you

traffic data quality analysis james sturrock, pe, ptoe ...floating car data collection 90-100%...

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